Camila Caiado, BSc in Statistics, PhD in Mathematical Sciences
- Statistics and Probability
- Statistics and Probability: Statistics
- Bayesian Statistics
- Parametric Inference
- Information Theory
- Stochastic Processes
- Howitt, Samuel H., Grant, Stuart W., Caiado, Camila, Carlson, Eric, Kwon, Dowan, Dimarakis, Ioannis, Malagon, Ignacio & McCollum, Charles (2018). The KDIGO acute kidney injury guidelines for cardiac surgery patients in critical care: a validation study. BMC Nephrology 19(1): 149.
- Ormerod, Paul & Caiado, Camila C. S. (2017). Market Structure with Interacting Consumers. Review of Behavioral Economics 4(1): 33-49.
- Bentley, R.A., Brock, W.A., Caiado, C.C.S. & O'Brien, M. (2016). Evaluating reproductive decisions as discrete choices under social influence. Philosophical Transactions of the Royal Society B: Biological Sciences 371(1692): 20150154.
- Caiado, C.C.S., Brock, W.A., Bentley, R.A. & O'Brien, M.J. (2016). Fitness landscapes among many options under social influence. Journal of Theoretical Biology 405: S0022-5193(16)00014-X, 5-16.
- Tang, Q., Hobbs, R.W., Zheng, C., Biescas, B. & Caiado, C.C.S. (2016). Markov Chain Monte Carlo inversion of temperature and salinity structure of an internal solitary wave packet from marine seismic data. Journal of Geophysical Research: Oceans 121(6): 3692-3709.
- Caiado, C.C.S. & Goldstein, M. (2015). Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points. Communications in Nonlinear Science and Numerical Simulation 26(1-3): 123-136.
- Bentley, R.A., Caiado, C.C.S. & Ormerod, P. (2014). Effects of memory on spatial heterogeneity in neutrally transmitted culture. Evolution and Human Behavior 35(4): 257-263.
- Brock, W.A., Bentley, R.A., O'Brien, M.J. & Caiado, C.C.S. (2014). Estimating a Path through a Map of Decision Making. PLoS ONE 9(11): e111022.
- Hickey, G.L., Grant, S.W., Caiado, C.C.S., Kendall, S., Dunning, J., Poullis, M., Buchan, I. & Bridgewater, B. (2013). Dynamic prediction modeling approaches for cardiac surgery. Circulation: Cardiovascular Quality and Outcomes 6(6): 649-658.
- Caiado, Camila C. S., Goldstein, Michael & Hobbs, Richard W. (2012). Bayesian Strategies to Assess Uncertainty in Velocity Models. Bayesian Analysis 7(1): 211-234.
- Bissell, J., Caiado, C.C.S., Curtis, S.E., Goldstein, M. & Straughan, B. (2015). Tipping Points: Modelling Social Problems and Health. Wiley.
Chapter in book
- Hickey, G.L., Grant, S.W., Caiado, C.C.S., Buchan, I. & Bridgewater, B. (2015). Cardiac Surgery Performance Monitoring. In Tipping Points: Modelling Social Problems an Health. Bissell, J., Caiado, C.C.S., Curtis, S.E., Goldstein, M. & Straughan, B. Wiley. 49.
- Caiado, C.C.S., Hickey, G.L., Grant, S.W., Goldstein, M., Markarian, G., McCollum, C. & Bridgewater, B. (2015). Heart Online Uncertainty and Stability Estimation. In Tipping Points: Modelling Social Problems an Health. Bissell, J., Caiado, C.C.S., Curtis, S.E., Goldstein, M. & Straughan, B. Wiley.
- Caiado, C.C.S. (2015). Stochastic Modelling for Compartmental Systems Applied to Social Problems. In Tipping Points: Modelling Social Problems an Health. Bissell, J., Caiado, C.C.S., Curtis, S.E., Goldstein, M. & Straughan, B. Wiley.
- Nakharutai, Nawapon, Troffaes, Matthias C. M. & Caiado, Camila C. C. S. (2017), Efficient algorithms for checking avoiding sure loss, in Antonucci, Alessandro, Corani, Giorgio, Couso, Inés & Destercke, Sébastien eds, Proceedings of Machine Learning Research 62: The Tenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA ’17). Lugano, Switzerland, PMLR, 241-252.
- Rathie, P.N., Swamee, P.K. & Caiado, C.C.S. (2008), A two parameter skew distribution function, Proceedings of the second World Aqua Congress World Aqua Congress (WAC2008). New Delhi, India.
- Rathie, P.N., Caiado, C.C.S. & Swamee, P.K. (2008), New intensity functions in hydraulic repairable systems, Proceedings of National Conference on Hydraulics and Water Resources National Conference on Hydraulics and Water Resources (Hydro 2008). Jaipur, India.
- Caiado, C.C.S. & Rathie, P.N. (2007), Polynomial Coefficients and Distribution of the Sum of Discrete Uniform Variables, in Mathai, A. M., Pathan, M. A. Jose, K. K. & Jacob, Joy eds, Eighth Annual Conference of the Society of Special Functions and their Applications. Pala, India, Society for Special Functions & their Applications, Pala.
- Rathie, P.N. & Caiado, C.C.S. (2007), Repairable Systems in Reliability Theory, Proceedings of the VI International Conference on Operational Research for Development International Conference on Operational Research for Development (ICORD VI). Fortaleza, Brazil, Fortaleza.
- Caiado, C.C.S. & Da-Silva, C.Q. (2006). Bayesian Inference in Non-Homogeneous Poisson Processes. Department of Statistics. Brasilia, Brazil.
- Caiado, C.S. & Rathie, P.N. (2005). Entropias e Índices Caudais. PIBIC/CNPq. Brasilia, Brazil.
- Caiado, C.C.S. & Rathie, P.N. (2005). Multinomial triangle coefficient and distribution of the sum of discrete uniform variates. Department of Statistics. Brasilia, Brazil.
- Caiado, C.S. & Rathie, P.N. (2004). Birthday Problem e Generalizações (The Birthday Problem and Generalizations). PIBIC/CNPq. Brasilia, Brazil.
My main research interests are in Bayesian approaches to modelling and uncertainty quantification. I am mostly interested in the development and implementation of models and the design of emulators (statistical representations) for large complex systems such as health, climate, and population dynamics. My current research is focused on multi-model uncertainty looking at frameworks for assimilating multiple models and experts’ beliefs, the aim of these frameworks is to unify multiple uncertainty specifications and provide an accessible decision support mechanism. This approach is essential when studying systems such as health where fast and reliable tools are necessary to aid decision making or such as climate where different modeling approaches are used by experts in different areas to inform policy makers. My current collaborations involve the development of Bayesian methods and their application to a number of areas including health, engineering, societal dynamics, climate, seismology, and banking. Most of these partnerships are generating substantial outputs with current and eminent impact in the local industry and society.